6 citations · 15 across the 4 of their papers we have counts for
6 papers
Goal-Guided Neural Cellular Automata: Learning to Control Self-Organising Systems
Shyam Sudhakaran, Elias Najarro, Sebastian Risi
Inspired by cellular growth and self-organization, Neural Cellular Automata (NCAs) have been capable of "growing" artificial cells into images, 3D structures, and even functional m…
HyperNCA: Growing Developmental Networks with Neural Cellular Automata
Elias Najarro, Shyam Sudhakaran, Claire Glanois +1
In contrast to deep reinforcement learning agents, biological neural networks are grown through a self-organized developmental process. Here we propose a new hypernetwork approach…
Variational Neural Cellular Automata
Rasmus Berg Palm, Miguel González-Duque, Shyam Sudhakaran +1
In nature, the process of cellular growth and differentiation has lead to an amazing diversity of organisms -- algae, starfish, giant sequoia, tardigrades, and orcas are all create…
MuSLCAT: Multi-Scale Multi-Level Convolutional Attention Transformer for Discriminative Music Modeling on Raw Waveforms
Kai Middlebrook, Shyam Sudhakaran, David Guy Brizan
In this work, we aim to improve the expressive capacity of waveform-based discriminative music networks by modeling both sequential (temporal) and hierarchical information in an ef…
Growing 3D Artefacts and Functional Machines with Neural Cellular Automata
Shyam Sudhakaran, Djordje Grbic, Siyan Li +4
Neural Cellular Automata (NCAs) have been proven effective in simulating morphogenetic processes, the continuous construction of complex structures from very few starting cells. Re…
Modeling natural language emergence with integral transform theory and reinforcement learning
Bohdan Khomtchouk, Shyam Sudhakaran
Zipf's law predicts a power-law relationship between word rank and frequency in language communication systems and has been widely reported in a variety of natural language process…